Customer and Business Analytics

by Daniel S. S. Putler, Robert E. Krider

Customer and Business Applied Data Mining for Business Decision Making Using R explains and demonstrates, via the accompanying open-source software, how advanced analytical tools can address various business problems. It also gives insight into some of the challenges faced when deploying these tools. Extensively classroom-tested, the text is ideal for students in customer and business analytics or applied data mining as well as professionals in small- to medium-sized organizations. The book offers an intuitive understanding of how different analytics algorithms work. Where necessary, the authors explain the underlying mathematics in an accessible manner. Each technique presented includes a detailed tutorial that enables hands-on experience with real data. The authors also discuss issues often encountered in applied data mining projects and present the CRISP-DM process model as a practical framework for organizing these projects. Showing how data mining can improve the performance of organizations, this book and its R-based software provide the skills and tools needed to successfully develop advanced analytics capabilities.

316 pages, Paperback

First published May 16, 2012

Reviews

[Mike Kruger · Rating 4 out of 5]

Good introduction to Customer analytics in a common business environment. Uses R software (free) with a custom overlay of R Commander, so the learning curve isn't too steep even if you have little familiarity with R. This is an analytics book, not a "big data" book, so the data sets aren't huge and there's no use of clickstream or frequent shopper data.

Designed as a textbook for upper level undergrads or MBA students, but OK for self-study.